A system and method for providing product research help to a consumer doing internet shopping. A consumer helper application for internet commerce has been designed to integrate the techniques that are currently used by many internet consumers into a single application program. For example, the consumer helper application allows a user to take notes, store web site links, store web site annotations, obtain collaborative input, and perform other tasks commonly used by web site consumers. The consumer helper application stores all of the information gathered in a single place. Information provided by other consumers may be shared using the consumer helper application. The consumer helper application will suggest specific items for a consumer to purchase based up on the information gathered by the consumer into the consumer helper application.
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8. A system comprising:
non-transitory memory storing instructions; and
one or more processors configured to execute the instructions to cause the system to perform operations comprising:
generating an annotation web page interface for assisting a plurality of users to perform research pertaining to a type of a product, the annotation web page interface comprising a features area comprising a selection feature and a set of selectable values corresponding to various features of different product types, the annotation web page further comprising a highlighting feature for annotating presentable information of a content page of a web site providing information about the product;
receiving, from a plurality of computer systems of the plurality of users using the annotation web page interface, a plurality of annotations of presentable information of the content page of the web site, the plurality of annotations including highlighting associated with portions of the presentable information;
determining, at a server, that a first portion of the presentable information includes good information corresponding to positive aspects of the product based on a first set of the plurality of annotations highlighting the first portion of the presentable information on the content page of the web site by selecting the first portion using the selection feature and designating the highlighted first portion as the good information using a first selectable value;
determining, at the server, that a second portion of the presentable information includes bad information corresponding to negative aspects of the product based on a second set of the plurality of annotations highlighting the second portion of the presentable information on the content page of the web site by selecting the second portion using the selection feature and designating the highlighted second portion as the bad information using a second selectable value;
based on an accessing of the content page of the web site by a first user of the plurality of users, generating, at the server for presentation to the first user, a collective highlighting of the presentable information, the collective highlighting including a designation of the first portion of the presentable information on the content page of the web site as the good information and a designation of the second portion of the presentable information on the content page of the web site as the bad information; and
presenting the content page of the web site to the first user including the collective highlighting.
15. A non-transitory machine readable medium embodying a set of instructions that, in response to being executed by one or more processors, cause performance of operations, the operations comprising:
generating an annotation web page interface for assisting a plurality of users to perform research pertaining to a type of a product, the annotation web page interface comprising a features area comprising a selection feature and a set of selectable values corresponding to various features of different product types, the annotation web page further comprising a highlighting feature for annotating presentable information of a content page of a web site providing information about the product;
receiving, from a plurality of computer systems of the plurality of users using the annotation web page interface, a plurality of annotations of presentable information of the content page of the web site, the plurality of annotations including highlighting associated with portions of the presentable information;
determining, at a server, that a first portion of the presentable information includes good information corresponding to positive aspects of the product based on a first set of the plurality of annotations highlighting the first portion of the presentable information on the content page of the web site by selecting the first portion using the selection feature and designating the highlighted first portion as the good information using a first selectable value;
determining, at the server, that a second portion of the presentable information includes bad information corresponding to negative aspects of the product based on a second set of the plurality of annotations highlighting the second portion of the presentable information on the content page of the web site by selecting the second portion using the selection feature and designating the highlighted second portion as the bad information using a second selectable value;
based on an accessing of the content page of the web site by a first user of the plurality of users, generating, at the server for presentation to the first user, a collective highlighting of the presentable information, the collective highlighting including a designation of the first portion of the presentable information on the content page of the web site as the good information and a designation of the second portion of the presentable information on the content page of the web site as the bad information; and
presenting the content page of the web site to the first user including the collective highlighting.
1. A method comprising:
generating an annotation web page interface for assisting a plurality of users to perform research pertaining to a type of a product, the annotation web page interface comprising a features area comprising a selection feature and a set of selectable values corresponding to various features of different product types, the annotation web page further comprising a highlighting feature for annotating presentable information of a content page of a web site providing information about the product;
receiving, from a plurality of computer systems of the plurality of users using the annotation web page interface, a plurality of annotations of presentable information of the content page of the web site, the plurality of annotations including highlighting associated with portions of the presentable information;
determining, at a server, that a first portion of the presentable information includes good information corresponding to positive aspects of the product based on a first set of the plurality of annotations highlighting the first portion of the presentable information on the content page of the web site by selecting the first portion using the selection feature and designating the highlighted first portion as the good information using a first selectable value;
determining, at the server, that a second portion of the presentable information includes bad information corresponding to negative aspects of the product based on a second set of the plurality of annotations highlighting the second portion of the presentable information on the content page of the web site by selecting the second portion using the selection feature and designating the highlighted second portion as the bad information using a second selectable value;
based on an accessing of the content page of the web site by a first user of the plurality of users, generating, at the server for presentation to the first user, a collective highlighting of the presentable information, the collective highlighting including a designation of the first portion of the presentable information on the content page of the web site as the good information and a designation of the second portion of the presentable information on the content page of the web site as the bad information; and
presenting the content page of the web site to the first user including the collective highlighting including the designation of the first portion of the presentable information on the content page of the web site as the good information and the designation of the second portion of the presentable information on the content page of the web site as the bad information.
2. The method of
3. The method of
4. The method of
identifying that a reference to a product is included in the bad information;
based on the identifying, decreasing a relevancy score of an additional content page, the additional content page pertaining to the product; and
based on the relevancy score not transgressing a threshold, preventing a link to the additional content page from being suggested to the first user.
5. The method of
identifying that a reference to a product is included in the good information;
based on the identifying, increasing a relevancy score of an additional content page, the additional content page pertaining to the product; and
based on the relevancy score transgressing a threshold, suggesting a link to the additional content page to the first user.
6. The method of
7. The method of
9. The system of
10. The system of
11. The system of
identifying that a reference to a product is included in the bad information;
based on the identifying, decreasing a relevancy score of an additional content page, the additional content page pertaining to the product; and
based on the relevancy score not transgressing a threshold, preventing a link to the additional content page from being suggested to the first user.
12. The system of
identifying that a reference to a product is included in the good information;
based on the identifying, increasing a relevancy score of an additional content page, the additional content page pertaining to the product; and
based on the relevancy score transgressing a threshold, suggesting a link to the additional content page to the first user.
13. The system of
14. The system of
16. The non-transitory machine readable medium of
17. The non-transitory machine readable medium of
18. The non-transitory machine readable medium of
identifying that a reference to a product is included in the bad information;
based on the identifying, decreasing a relevancy score of an additional content page, the additional content page pertaining to the product; and
based on the relevancy score not transgressing a threshold, preventing a link to the additional content page from being suggested to the first user.
19. The non-transitory machine readable medium of
identifying that a reference to a product is included in the good information;
based on the identifying, increasing a relevancy score of an additional content page, the additional content page pertaining to the product; and
based on the relevancy score transgressing a threshold, suggesting a link to the additional content page to the first user.
20. The non-transitory machine readable medium of
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This application is a continuation of U.S. application Ser. No. 12/133,100, filed Jun. 4, 2008, and entitled, “SYSTEM AND METHOD FOR COMMUNITY AIDED RESEARCH AND SHOPPING,” which is incorporated herein by reference in its entirety.
The present invention relates to the field of internet commerce. In particular, but not by way of limitation, the present invention discloses techniques for allowing an internet consumer to easily perform product research.
The World Wide Web aspect of the global internet has become a vast commercial marketplace where a consumer can find just about every type of product available. Even the traditional start of the holiday shopping season, the day after Thanksgiving known as “Black Friday”, now has an internet corollary: Cyber Monday, the first Monday after the Thanksgiving Holiday.
Although internet commerce has been taking place for many years now, the industry is still in a relative infancy compared to normal stores and open air markets. Many people are still reluctant to use internet retail web sites since they do not feel familiar enough and they do not feel they can easily get the information needed to make good purchasing decisions. Even veteran internet shoppers can have difficulties in find the information that they need to make a good educated purchasing decision
In the drawings, which are not necessarily drawn to scale, like numerals describe substantially similar components throughout the several views. Like numerals having different letter suffixes represent different instances of substantially similar components. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document.
The following detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show illustrations in accordance with example embodiments. These embodiments, which are also referred to herein as “examples,” are described in enough detail to enable those skilled in the art to practice the invention. It will be apparent to one skilled in the art that specific details in the example embodiments are not required in order to practice the present invention. For example, although the example embodiments are mainly disclosed with reference to email systems that use the Simple Mail Transport Protocol (SMTP), the teachings can be used with other types of email protocols or other types of electronic communication systems. The example embodiments may be combined, other embodiments may be utilized, or structural, logical and electrical changes may be made without departing from the scope what is claimed. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope is defined by the appended claims and their equivalents.
In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one. In this document, the term “or” is used to refer to a nonexclusive or, such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. Furthermore, all publications, patents, and patent documents referred to in this document are incorporated by reference herein in their entirety, as though individually incorporated by reference. In the event of inconsistent usages between this document and those documents so incorporated by reference, the usage in the incorporated reference(s) should be considered supplementary to that of this document; for irreconcilable inconsistencies, the usage in this document controls.
Computer Systems
The example computer system 100 illustrated in
The disk drive unit 116 includes a machine-readable medium 122 on which is stored one or more sets of computer instructions and data structures (e.g., instructions 124 also known as ‘software’) embodying or utilized by any one or more of the methodologies or functions described herein. The instructions 124 may also reside, completely or at least partially, within the main memory 104 and/or within the processor 102 during execution thereof by the computer system 100, the main memory 104 and the processor 102 also constituting machine-readable media.
The instructions 124 for operating computer system 100 may be transmitted or received over a network 126 via the network interface device 120 utilizing any one of a number of well-known transfer protocols such as the File Transfer Protocol (FTP).
While the machine-readable medium 122 is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “machine-readable medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies described herein, or that is capable of storing, encoding or carrying data structures utilized by or associated with such a set of instructions. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical media, flash memory, magnetic media, and carrier wave signals.
For the purposes of this specification, the term “module” includes an identifiable portion of computer code, computational or executable instructions, data, or computational object to achieve a particular function, operation, processing, or procedure. A module need not be implemented in software; a module may be implemented in software, hardware/circuitry, or a combination of software and hardware.
Internet Commerce Systems
An Application Program Interface (API) server 214 and a web server 216 are coupled to, and provide programmatic and web interfaces respectively to, one or more application servers 218. The application server(s) 218 host one or more marketplace applications such as commerce applications 220 and payment applications 222. The application server(s) 218 are, in turn, shown to be coupled to one or more database servers 224 that facilitate access to one or more databases 226.
The commerce applications 220 may provide a number of marketplace functions and services to users that access the networked system 202. The payment applications 222 may likewise provide a number of payment services and functions to users. The payment applications 222 may allow users to accumulate value (e.g., in a commercial currency, such as the U.S. dollar, or a proprietary currency, such as “points”) in accounts, and then later to redeem the accumulated value for products (e.g., goods or services) that are made available via the marketplace applications 220. While the marketplace and payment applications 220 and 222 are shown in
Further, while the system 200 shown in
The web client 206 accesses the various commerce application(s) 220 and payment application(s) 222 via the web interface supported by the web server 216. Similarly, the programmatic client 208 accesses the various services and functions provided by the marketplace and payment applications 220 and 222 via the programmatic interface provided by the API server 214. The programmatic client 208 may be a seller application to enable sellers to author and manage listings on the networked system 202 in an off-line manner, and to perform batch-mode communications between the programmatic client 208 and the networked system 202. One example of such an application is the TurboLister application developed by eBay Inc., of San Jose, Calif.
Shopping with Internet Commerce Web Sites
Most internet commerce is currently conducted by a consumer running a web browser application on a personal computer that accesses a web server application implementing an internet commerce site. If the consumer happens to know the exact item that the consumer wishes to purchase then that consumer can simply enter the name of the desired product into a search box at an internet commerce site or into a generalized internet search engine.
However, most people do not know exactly what they wish to purchase when initially shopping for an item. Instead, the consumer will have a rough idea of what the consumer wishes to purchase. For example, a consumer may wish to purchase a digital camera but not much more detail than that. The consumer may have a budget and some rough specifications in mind such as a budget of $300 and a camera with a resolution greater than 4 megapixels. But beyond that, the user will do additional research and browsing to identify the camera to purchase.
On the Internet, the consumer may visit published review sites like cnet.com or user review sites like epinions.com in order to obtain reviews for some products. For example, computer system 310 running internet browser application 306 in
Beyond computer-based shopping research, a consumer may talk to friends and colleagues to get additional information and recommendations. A consumer may also read traditional magazines and newspapers to learn about available products. Keeping track of all the information gained during this shopping research phase is difficult. The information may be spread across hand written notes on scraps of paper, articles cut from magazines and newspapers, the Uniform Resource Locator (URL) based “bookmarks” in the consumer's internet web browser, and in the consumer's memory.
After having collected all of this shopping research information, the consumer must then somehow consolidate all this information gathered during the shopping research phase. The consumer then analyzes the consolidated shopping research information in order to pick a specific product to purchase.
After selecting a particular product, the consumer must visit various web sites to find a good price on the desired item. Referring to
This entire online shopping process has many shortcomings. For example, the process is not guided, information may easily become lost or forgotten, it is difficult to integrate collaborative input (such as the advice of friends/colleagues) into the process, and the gathered information is not organized or easily stored.
Consumer Helper Application for Internet Commerce Overview
To improve upon the consumer experience for internet shopping, this disclosure introduces a consumer helper application for internet commerce. The consumer helper application has been designed to integrate the techniques that are currently used by many internet consumers into a single application program. For example, the consumer helper application allows a user to take notes, store web site links, store web site annotations, obtain collaborative input, and perform other tasks commonly used by web site consumers. The consumer helper application stores all of the information gathered in a single place. Finally, the consumer helper application will suggest specific items for a consumer to purchase based up on the information gathered by the consumer into the consumer helper application.
Consumer Helper Application for Internet Commerce Architecture
In the consumer helper application system of
In addition to the consumer helper application plug-in 307 on the user's computer, a consumer helper server application 314 is available on a network 304 such as the internet. Consumer helper server application 314 can provide the user with a starting point and an initial set of data that a user can use when research a prospective purchase. The consumer helper server application 314 has an associated consumer helper database 326 for storing information collected and generated by users of the consumer helper application system. Consumer helper server application 314 may also reference external data sources such as commerce databases 328 or internet commerce server 280.
Consumer Helper Application Operation
To best describe the operation of the consumer helper application, an example usage of the consumer helper application will be disclosed with reference to
As part of the initiation of a new product research project, the consumer may be requested to specify how much of the consumer's information may be shared with other users of the shopping research system. The sharing of the consumer's information may be done on a completely anonymous basis such that no privacy is lost.
In one embodiment, the system provides a detailed set of information sharing preferences that allow a consumer to select between the following access control selections: private, global, targeted share, whole or selective share. If the consumer does not wish to share any information and thus wishes to keep all the information that the consumer is entering private completely to himself/herself, then the user will select “private”. If the user does not mind sharing their information with everyone else that uses the system, then the consumer can select “global”. If the consumer wishes to share their information with a particular user or a selected set of users then the consumer may select “targeted share”. A consumer may further select the specific information that is shared such that if a consumer wishes to share all the information, then the consumer selects “whole” but if the user only wishes to share some of the information then the consumer will select “selective”.
After starting a new research project at step 410, the consumer selects a particular type of product being researched, at step 415. In one embodiment, a set of templates for different product types are available. If a template for a specific product type is not available, a user may select a generic product type template. If enough consumers seek the same type of product that does not have a template available, then a template may be created for that product type which is in demand.
Similarly, if a user wishes to add a new type of feature to the features area 520 for the current product type, the consumer may select “Add your own” link 531 to add a new type of feature for that product type. A set of user interfaces will allow the user to specify the name of the feature and a set of possible values for the new feature. This newly added feature and the rest of the consumer's choices are stored within consumer helper database 326. A data-mining application 332 can be used to continually review the contents of the consumer helper database 326. In this manner, the data-mining application 332 can identify any patterns or clusters the form within the consumer helper database 326. For example, if several different consumers all add a new feature called “image resolution” to the digital camera template then the data-mining application 332 will suggest to an administrator that a new feature called “image resolution” be added to the standard template for digital camera products.
Referring back to
In addition to selecting web sites and products that may be of interest to the consumer, step 430 may also be used to select advertisements that may be of interest to the consumer. Specifically, advertisements from manufacturers or retailers of products that the consumer has expressed an interest in may be selected and added to subsequent displays that will be presented to the consumer. Do the amount of information available at 430 very sophisticated advertising targeting may be performed with the system of the present disclosure. Specifically, these consumers have expressed an interest in purchasing a product and a great deal of information about the specific type of product that the consumer is interested is available for use in selecting an advertisement. With such detailed information available on the users of the system who are by their use of the system interested in purchasing a product, the value of the advertising opportunities will be very high.
Referring back to
In
If a consumer has specified that the consumer's data may be shared with other users, then the system may automatically make the consumer's notes available to other users of the system. Alternatively, a system administrator may review various notes entered and decide which notes entered by a consumer to available to other users of this system. In this manner, the best research notes entered by any user may be shared with other users looking for the same type of item.
In one embodiment a shared “Questions & Answers” section is created for each product type. In the Questions & Answers section, various users may post questions that may be read by other users. This may be performed in the same manner that a user enters notes except that the note with the question will immediately be made available to other users of the system. For example, in the digital camera Questions & Answers section, a user may post a note with question “Is Canon D80 better than Z43 in low light condition?” Other users may then directly answer the question with another posting. Other users might attach questions to their publically posted notes and bookmarks (such as questions that are answered by the note) such that other users that have the same questions can locate the answers quickly.
In one embodiment, the system might examine a question that a user is posting and attempt to match the user's question to similar questions already answered and recommend those answers to the user before allowing a new question to be posted. In this manner, the system will prevent the same questions from being asked and answered repeatedly. Similarly, the system may match a user question to related answers (i.e. “see also”).
Referring to
At step 430, the system again generates a set of web sites and products that may be of interest to the consumer. Since the consumer may have entered new notes at step 460, the consumer helper application may consider these new notes when re-generating a set of web sites and products of interest. For example, a user may have entered the name of a particular name brand manufacturer in the notes such that a web site associated with that manufacturer may be added to the list of web sites of interest. Similarly, products made by that particular manufacture may receive an increased relevancy score such that those products will be displayed higher on a list of products of interest.
Referring again to
The other research type links 650 of will cause other sets of web research sites to be displayed. For example, if the consumer selects the “Reviews” link from research type links 650 then the set of product review sites illustrated in
Referring back to the buying guides research view
The consumer may visit any of the suggested web sites in order to learn more information about the desired product. Referring again to
For example,
Note that as long as the example consumer helper toolbar is available, it can be used at any time during the consumer's web browsing. Thus, if a friend sends the user a link to a useful web page for the product the user is researching then the consumer can select the “store page” button 702 to store that web page into the consumer helper application. The consumer helper application may ask the user to specify if the web page is a buying guide, a product review, a FAQ, or any other type of web page in order to place the web page in proper area of the reviews section illustrated in
The consumer helper application plug-in may store the link to that web page into the consumer helper database 326. If data-mining application 332 notices that several different consumers researching the same type of product add the same web page, then the data-mining application 332 may automatically add that web page as a standard suggested web page for that product type. Alternatively, the data-mining application 332 may suggest to an administrator that the popular web site be added to the set of standard suggested web pages for that product type.
The “The Good” button 703 and the “The Bad” button 704 in
The consumer helper application plug-in may store the high-lighting of a web page into the consumer helper database 326 such that the information may be shared among all the user of the consumer helper application. For example, the data-mining application 332 may determine which sections of the various stored web pages have been highlighted by many users. The consumer helper application may then allow a consumer to use this information by displaying those most high-lighted sections with high-lighting that may be in a different color. In this manner the collective high-lighting of many different consumers researching the same type of product on the same web page can be used to show the aspect that many consumers have found to be important
After storing user annotations to a web site and returning to the product research page, the system may generate a new set of web sites of interest at step 430. The system may use any additional information store while the consumer was browsing web sites to help re-generate a set of web sites and products of interest. For example, the system may attempt to locate web sites and products that include keywords from text that a consumer high-lighted using “The Good” button 703. Similarly, the system may eliminate or lower the relevancy score of products that contain keywords in text that the consumer high-lighted using “The Bad” button 704. After re-generating the set of web sites and products of interest at step 430 the system proceeds to step 440 to display the user interface with user notes, web sites of interest, and suggested products for the consumer.
Numbers factors can be used to select and filter the products that will appear in the suggest items view of
In the embodiment illustrated in
The preceding description is intended to be illustrative, and not restrictive. For example, the above-described embodiments (or one or more aspects thereof) may be used in combination with each other. Other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of the claims should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Also, in the following claims, the terms “including” and “comprising” are open-ended, that is, a system, device, article, or process that includes elements in addition to those listed after such a term in a claim are still deemed to fall within the scope of that claim. Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects.
The Abstract is provided to comply with 37 C.F.R. § 1.72(b), which requires that it allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Also, in the above Detailed Description, various features may be grouped together to streamline the disclosure. This should not be interpreted as intending that an unclaimed disclosed feature is essential to any claim. Rather, inventive subject matter may lie in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.
Sundaresan, Neelakantan, Nguyen, Hill Trung, Ruvini, Jean-David, Sarwar, Badrul M.
Patent | Priority | Assignee | Title |
Patent | Priority | Assignee | Title |
7043443, | Mar 31 2000 | Kioba Processing, LLC | Method and system for matching potential employees and potential employers over a network |
7512551, | Jun 23 1999 | Signature Systems LLC | Method and system for implementing a search engine with reward components and payment components |
7536323, | Mar 26 2003 | CHEMTRON RESEARCH LLC | Online intelligent multilingual comparison-shop agents for wireless networks |
8538821, | Jun 04 2008 | PayPal, Inc | System and method for community aided research and shopping |
20030028585, | |||
20030177121, | |||
20030177202, | |||
20030227479, | |||
20050216913, | |||
20050234958, | |||
20060026147, | |||
20070023515, | |||
20080071829, | |||
20080140506, | |||
20080183753, | |||
20080222295, | |||
20080243586, | |||
20080255978, | |||
20090089678, | |||
20090171813, | |||
20090210244, | |||
20090299667, | |||
20090307100, | |||
20090313088, | |||
20100042511, |
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May 12 2008 | RUVINI, JEAN-DAVID | eBay Inc | ASSIGNMENT OF ASSIGNORS INTEREST SEE DOCUMENT FOR DETAILS | 031215 | /0376 | |
May 12 2008 | SARWAR, BADRUL M | eBay Inc | ASSIGNMENT OF ASSIGNORS INTEREST SEE DOCUMENT FOR DETAILS | 031215 | /0376 | |
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